Systems and Methods for Utilizing Machine-Assisted Vehicle Inspection to Identify Insurance Buildup or Fraud

ABSTRACT

A remotely-controlled (RC) and/or autonomously operated inspection device, such as a ground vehicle or drone, may capture one or more sets of imaging data indicative of at least a portion of an automotive vehicle, such as all or a portion of the undercarriage. The one or more sets of imaging data may be analyzed based upon data indicative of at least one of vehicle damage or a vehicle defect being shown in the one or more sets of imaging data. Based upon the analyzing of the one or more sets of imaging data, damage to the vehicle or a defect of the vehicle may be identified. The identified damage or defect may be compared to a claimed damage or defect to determine whether the claimed damage or defect occurred.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of, and claims the benefit of, U.S.patent application Ser. No. 15/843,761, filed Dec. 15, 2017 and entitled“Systems and Methods for Utilizing Machine-Assisted Vehicle Inspectionto Identify Insurance Buildup or Fraud,” the entire disclosure of whichis incorporated herein by reference.

This application further claims priority to and the benefit of thefiling date of provisional U.S. Application Ser. No. 62/438,769, filedDec. 23, 2016 and entitled “Systems and Methods for Machine-AssistedVehicle Inspection,” the entire disclosure of which is incorporatedherein by reference.

FIELD OF THE INVENTION

The present disclosure generally relates to machine-assisted vehicleinspection. More particularly, the present disclosure relates toidentifying damages to or defects of vehicles via a computerizedanalysis of one or sets of imaging data captured by aremotely-controlled and/or autonomously operated vehicle, drone, orother inspection device.

BACKGROUND

Conventionally, inspection of a vehicle for damages and/or defectsinvolves manual processes. A mechanic, for example, the mechanic mayinspect the body and/or undercarriage of the vehicle. By inspecting thevehicle, the mechanic may identify, for example, aesthetic or functionaldamages to the vehicle, parts in need of replacement/repair, vehiclealignment issues, and/or other damage to the vehicle or defects of thevehicle. After identifying damage and/or a defect, the mechanic maydetermine remedial steps to correct the damage or defect (e.g.,correction of wheel alignment, repair of a vehicle part, ordering areplacement vehicle part, etc.).

These manual processes, however, may incur high equipment and laborcosts. For example, any inspection of a vehicle may require a mechanicto move the vehicle from its current location (e.g., a parking lot) to amore appropriate location (e.g., a repair bay of an automotive repairshop) that offers more physical space and equipment for vehicleinspection. As another example, a complete and accurate inspection ofthe vehicle undercarriage may require a means for elevating the vehicle(e.g., a vehicle lift). Furthermore, the costs of any vehicle inspectionprocesses are, naturally, subject to labor costs associated with themechanics or technicians performing the processes.

After inspecting the vehicle, a mechanic may estimate a cost or partsnecessary for a service or repair. Alternatively, the mechanic maymanually input results of the inspection into a tool to do the same.However, if the mechanic has misidentified or failed to identify adamage or defect of the vehicle, the mechanic or the tool may provide aninaccurate estimate.

SUMMARY

The present aspects may be generally related to utilization ofremotely-controlled (RC) and/or autonomously operated inspection devices(e.g., RC or autonomously operated cars or drones to identify damage toa vehicle and/or a defect of the vehicle. The inspection device maycapture one or more sets of imaging data indicative of at least aportion of the vehicle. The one or more sets of imaging data may beanalyzed based upon data indicative of vehicle damage and/or a vehicledefect. Based upon the analysis of the one or more sets of imaging data,at least one of damage to the vehicle or a defect of the vehicle may beidentified.

In one embodiment, a computer-implemented method may be provided. Themethod may include (1) analyzing, via one or more processors, one ormore sets of imaging data to identify at least one of damage to avehicle or a defect of the vehicle, (2) analyzing, via the one or moreprocessors, the identified at least one of the damage to the vehicle ordefect of the vehicle with respect to reported damage indicated in aninsurance claim, to determine whether the reported damage indicated inthe insurance claim is accurate, (3) in response to determining that thereported damage to the vehicle is accurate, processing, via the one ormore processors, the insurance claim, and/or (4) transmitting, via theone or more processors or via one or more transceivers, to a mobiledevice, an indication of the identified at least one of the damage orthe defect. The method may include additional, alternate, or fewerelements, including those described herein.

In another embodiment, a computer system may be provided. The computersystem may include (1) one or more processors; and (2) one or morememories storing computer-executable instructions that, when executed bythe one or more processors, cause the computer system to (i) analyze,via the one or more processors, one or more sets of imaging data toidentify at least one of damage to a vehicle or a defect of the vehicle;(ii) analyze, via the one or more processors, the identified at leastone of the damage to the vehicle or defect of the vehicle with respectto reported damage indicated in an insurance claim, to determine whetherthe reported damage indicated in the insurance claim is accurate; (iii)in response to determining that the reported damage to the vehicle isaccurate, process, via the one or more processors, the insurance claim;and/or (iv) transmit, via the one or more processors or via one or moretransceivers, to a mobile device, an indication of the identified atleast one of the damage or the defect. The computer system may includeadditional, less, or alternate functionality and components, includingthose discussed elsewhere herein.

In yet another embodiment, one or more non-transitory computer readablemedia may be provided. The one or more non-transitory computer readablemedia may store non-transitory computer executable instructions that,when executed via one or more processors of a computer, cause thecomputer to (1) analyze, via the one or more processors, one or moresets of imaging data to identify at least one of damage to a vehicle ora defect of the vehicle, (2) analyze, via the one or more processors,the identified at least one of the damage to the vehicle or defect ofthe vehicle with respect to reported damage indicated in an insuranceclaim, to determine whether the reported damage indicated in theinsurance claim is accurate, (3) in response to determining that thereported damage to the vehicle is accurate, process, via the one or moreprocessors, the insurance claim, and/or (4) transmit, via the one ormore processors or via one or more transceivers, to a mobile device, anindication of the identified at least one of the damage or the defect.The non-transitory computer executable instructions may includeadditional, fewer, or alternate instructions, including those describedherein.

BRIEF DESCRIPTION OF THE DRAWINGS

Advantages will become more apparent to those skilled in the art fromthe following description of the preferred aspects which have been shownand described by way of illustration. As will be realized, the presentaspects may be capable of other and different aspects, and their detailsare capable of modification in various respects. Accordingly, thedrawings and description are to be regarded as illustrative in natureand not as restrictive.

The figures described below depict various aspects of the applications,methods, and systems disclosed herein. It should be understood that eachfigure depicts an aspect of a particular aspect of the disclosedapplications, systems and methods, and that each of the figures isintended to accord with a possible aspect thereof. Furthermore, whereverpossible, the following description refers to the reference numeralsincluded in the following figures, in which features depicted inmultiple figures are designated with consistent reference numerals.

FIGS. 1a-1b illustrate profile and undercarriage views of a damagedand/or defective vehicle in accordance with exemplary aspects of thepresent disclosure;

FIG. 2 illustrates a damaged and/or defective situated in a parking lotin accordance with an exemplary aspect of the present disclosure;

FIG. 3 depicts an exemplary computer system for inspecting a damagedand/or defective vehicle in accordance with an exemplary aspect of thepresent disclosure;

FIGS. 4a-4b depict overhead and profile views of a vehicle inspected byan inspection device in accordance with exemplary aspects of the presentdisclosure;

FIG. 5 illustrates a flow diagram of an exemplary computer-implementedmethod for identifying at least one of damage to a vehicle or a defectof the vehicle in accordance with an exemplary aspect of the presentdisclosure;

FIG. 6 illustrates a flow diagram of an exemplary computer-implementedmethod for verifying a vehicle insurance claim in accordance with anexemplary aspect of the present disclosure; and

FIG. 7 illustrates a flow diagram of an exemplary computer-implementedmethod for identifying at least one of damage to a present vehicle or adefect of the present vehicle damage based upon training sets of imagingdata indicative of reference vehicles in accordance with an exemplaryaspect of the present disclosure.

DETAILED DESCRIPTION

Referring to FIG. 1a , a profile view 120 of an example automotivevehicle 124 is shown. The automotive vehicle 124 (e.g., a car, truck, ormotorcycle) may experience damage or acquire a defect over the course ofnormal operation, or as a result of a particular event (e.g., a singleor multi-car collision, inclement weather, vandalism, etc.). Damage tothe vehicle 124 may include, for example, a window 130 sustaining acrack or break 132, and/or a rear bumper 136 sustaining a dent 138, asis illustrated in FIG. 1a . Various other damage to the vehicle ordefects of the vehicle (e.g., a broken or defective headlight/taillight,a dented door, a flat tire, a cracked windshield, etc.) is possible.

Referring now to FIG. 1b , the vehicle 124, when viewed from anundercarriage (i.e., from beneath) view 140, may exhibit damage to itsundercarriage or a defect of the undercarriage. For example, damage tothe vehicle 124 may include the axle 144 having a break 148, as is shownin FIG. 1b . Various other undercarriage damages or defects (e.g., apoor wheel alignment, a pierced and/or dented undercarriage part, etc.),are possible.

Conventionally, the inspection of a vehicle (e.g., the vehicle 124) forsuch damages and defects is a manual process. A mechanic, for example,may visually inspect the body and/or undercarriage of the vehicle 124from views similar to the profile view 120 and the undercarriage view140, respectively, to identify damage to and/or one or more defects ofthe vehicle 124.

After identifying damage to the vehicle 124 or a defect of the vehicle124, the mechanic may recommend a service or repair (e.g., alignmentcorrection, part replacement, or part repair) that may remedy the one ormore damages and/or defects. Additionally or alternatively, the mechanicmay manually input his or her observations into a computer program thatwill similarly provide output of a recommended service or repair.Recommendation of a service or repair may include an estimated costand/or an estimated time frame for completion of the service or repair.

These manual inspection processes, however, have notable disadvantagesand limitations. One disadvantage in particular is evident from FIG. 2,which depicts the vehicle 124 situated in a parking lot 200 andsurrounded by other vehicles 204 a-204 d. In practice, it is common fora damaged vehicle to be stored in a parking lot or another crowded areauntil it can be manually inspected. Conventionally, before the vehicle124 can be inspected, the vehicle 124 must be moved from the parking lot200 into a repair bay of a repair shop, for example, or at least to anarea of space open enough for the mechanic to comfortably inspect thevehicle from the necessary views.

Further, inspection of the undercarriage of the vehicle 124 may requireuse of specialized machinery (e.g., a vehicle lift for elevating thevehicle 124) such that the vehicle 124 may be viewed from below (i.e.,the undercarriage view 140). Thus, inspection of the undercarriage ofthe vehicle 124 may require that the vehicle 124 be moved into a repairbay where the specialized machinery is located. In effect, if thevehicle 124 is not geographically located near a shop with suchmachinery, it may be exceedingly difficult or even impossible for amechanic to manually inspect the undercarriage of the vehicle 124without driving or transporting the vehicle 124 a significant distance.

Accordingly, manual inspection of the vehicle 124 may introducesignificant costs and delays. Cost of inspection equipment, time spentmoving and manually inspecting the vehicle, and cost of a mechanic'slabor may significantly increase the cost of a vehicle diagnosis,service, and/or repair.

The systems and methods described herein address at least thesedeficiencies in the field of automotive vehicle inspection. Using thesystems and methods described herein, damages to vehicles and defects ofvehicles may be identified and remedied more quickly and easily.Utilizing an imaging-enabled inspection device (e.g., aremotely-controlled and/or autonomously operated airborne or groundinspection device), one or more sets of imaging data (also referred toas “images”) of a vehicle (e.g., the vehicle 124) may be captured andautomatically analyzed to identify one or more damages or defects of thevehicle 124.

Generally, the small size and high maneuverability of the inspectiondevice may allow the inspection device to easily move above the vehicle124, below the vehicle 124, and/or between the vehicle 124 and anotherobject (e.g., the vehicle 204 a and/or another nearby vehicle(s) orobject(s)), without requiring the vehicle 124 to be repositioned orhoisted by a vehicle lift. Further, the inspection device may even betransported to a current location of the vehicle (e.g., by a mechanic oran insurance estimator), and thus the vehicle may not need to betransported to a particular location (e.g., a repair bay of a repairshop) for inspection.

Accordingly, among other advantages and improvements, the presentaspects improve an existing technological process in the field ofautomotive vehicle inspection. For instance, the present aspects moreparticularly improve the technological process of inspecting a vehiclefor damage and defects by utilizing an autonomously operated and/orremote-controlled inspection device to capture and analyze images of avehicle to automatically identify damage to a vehicle or a defect of thevehicle, and thereby provide advantages over conventional inspectiontechniques such as the advantages described above.

Machine-Assisted Vehicle Inspection System

FIG. 3 depicts an example computer system 300 that may be used toinspect an automotive vehicle (e.g., the vehicle 124) to identify one ormore damages or defects of the vehicle 124. The system 300 may includean image analysis system 320, a vehicle inspection device 350, thevehicle 124, a mobile device 380, a controller unit 390, and/or othercomponents, which may communicate over one or more communicationnetworks 370, such as via wireless communication or data transmissionover one or more radio frequency links or digital communicationchannels.

In this detailed description, reference will be made to the vehicle 124depicted in the drawings, which may be a car. However, it should beunderstood in light of the teaching and disclosure herein that thevehicle 124 may be, for example, a truck, a motorcycle, a bus, or anyother suitable automotive vehicle.

The inspection device 350 may be used to inspect the vehicle 124.Generally, the inspection device 350 may be any imaging-enabled devicethat may move around, over, and/or below the vehicle 124 to capture oneor more images of at least a portion of the vehicle 124 (e.g., a face ofthe vehicle 124, a specific part, a number of parts of a specific type,etc.).

For example, in some aspects, the inspection device 350 may be aremotely-controlled (RC) and/or autonomously operated ground inspectiondevice (e.g., an RC car). A computer program or a human operator, forexample, may direct the inspection device 350 to circle about thevehicle 124 on the ground to capture one or more images of the front,rear, and/or sides of the vehicle 124. Alternatively or additionally, ifthe inspection device is short enough in height, the program or operatormay control the inspection device to position itself underneath thevehicle 124 to capture one or more images of the undercarriage (e.g.,the chassis, which may include the engine, axles, transmission,suspension, and/or exhaust, among other parts) of the vehicle 124.Further, if the inspection device is taller in height (or if height isadjustable) the inspection device may also or alternatively be elevatedto capture one or more images of the top (e.g., hood, windshield, and/orroof) of the vehicle 124.

In some aspects, the inspection device 350 may be a remotely-controlledand/or autonomously operated airborne inspection device (e.g., a droneor nano drone). A computer program or a human operator, for example, maydirect the inspection device 350 to fly over and/or around the vehicle124 to capture one or more images of at least a portion of the vehicle124 (e.g., the front, rear, sides, and/or top), such as via wirelesscommunication or data transmission over one or more radio frequencylinks or digital communication channels.

In any case, the inspection device 350 may include an imaging unit 352(e.g., a camera). The imaging unit 352 may be temporarily affixed (e.g.,within a device holder) or included permanently as a part of theinspection device 350 in any suitable configuration (e.g., situated ontop of the inspection device 350, hanging from the bottom of theinspection device 350, etc.) such that the inspection device 350 maycapture one or more images of the vehicle 124. The imaging unit 352 maybe for example, a still image or video camera device, a lidar (laserremote sensing) device, a radar device, a sonar device, a thermalimaging device, or some combination of the above (e.g., a video cameradevice additionally including lidar and thermal imaging capabilities).Accordingly, the imaging unit 352 may be configured to capture any oneor more types of images (e.g., analog or digital photographs, thermalimages, lidar scans, radar images, sonar images, etc.), and the imagesmay include still photographs, video, or some combination of the two.Further, in one aspect, the imaging unit 352 may utilize specialtyimaging equipment such as a specialty lens (e.g., a wide-angle “fisheye”lens), as will be discussed herein.

Operation of the inspection device 350 (including movement and/or imagecapturing) may be controlled in any of a number of suitable manners. Insome aspects, a human operator may operate the inspection device via thecontroller unit 390, which may communicate with the inspection device350 via the one or more networks 370 (which may be one or more wiredand/or wireless networks, public and/or private networks, using anycommunication standard or technology), such as via wirelesscommunication or data transmission over one or more radio frequencylinks or digital communication channels. In other aspects, one or morememories 354 of the inspection device 350 may include operationinstructions that, when executed on one or more processors 356 of theinspection device 350, may cause the inspection device 350 to inspectthe vehicle 124 according to the operation instructions (e.g., byperformance of one or more inspection actions such as those describedherein). In one aspect, the operation instructions may include static,precise instructions for movement of the inspection device 350 and/orfor image capturing using the imaging unit 352 (e.g., to capture the oneor more images at a particular time or frequency). Additionally oralternatively, the operation instructions may enable the inspectiondevice 350 to move autonomously (e.g., moving in response to thelocation of the vehicle 124 and/or nearby obstacles detected via theimaging unit 352) and/or capture the one or more images in response tostimuli or objects detected via the imaging unit 352. Additionally oralternatively, operation instructions may be stored at the imageanalysis system 320, and the image analysis system 320 may cause, viaone or more processors 326 and the one or more networks 370, the imagingunit 352 to capture one or more images of at least a portion of thevehicle 124.

Combinations of two or more of the above-described techniques foroperation of the inspection device 350 may be used. For example,movement of the inspection device 350 may proceed according toinstructions stored at the one or more memories 354, while imagecapturing may be controlled by a human operator via the controller unit390. As another example, operation instructions may be stored at theinspection device 350, but the image analysis system 320 may cause theinstructions to be executed at the inspection device 350.

In any case, in operation, the inspection device 350 may capture one ormore images of the vehicle 124 via the imaging unit 352. The inspectiondevice 350 may store the one or more images at the one or more memories354, to which the imaging unit 352 may be communicatively connected viaa system bus 362. The inspection device 350 may be configured to storethe one or more images at the one or more memories 354 until the one ormore images are e manually retrieved by an operator (e.g., by removal ofa removable storage by a mechanic or insurance representative).Alternatively or additionally, the inspection device 350 may beconfigured to automatically transmit the one or more images via anetwork interface 360 (which may include one or more transceivers) andthe one or more networks 370 to the image analysis system 320.

The image analysis system 320 may include one or more memories, whichmay include one or more program memories 322 storing one or moreprograms 323, and/or one or more random access memories (RAMs) 324. Theone or more programs 323 may include computer-executable instructionsthat, when executed on the one or more processors 326, cause the imageanalysis system 320 to perform the operations described herein.Additionally, or alternatively, a user may utilize a user interface (UI)328 to cause (e.g., via a mouse interaction, a key stroke, voicecommand, motion gesture, etc.) the image analysis system 320 to performthe operations described herein.

Generally, the image analysis system 320 may be configured toautomatically analyze one or more images of the vehicle 124 to identifydamage to the vehicle 124 (e.g., body, undercarriage, or other partdamage) and/or one or more defects of the vehicle 124 (e.g., a defectivepart or an improper wheel alignment). The image analysis system 320 maybe configured to perform alternative or additional actions, includingactions described herein. For example, the image analysis system 320 maycause, via the one or more processors 326 and/or one or moretransceivers, one or more images of at least a portion of the vehicle124 to be captured by the imaging unit 352 of the inspection device 350.

The image analysis system 320 may be configured to receive, via one ormore network interfaces 336 and the one or more networks 370, one ormore images of the vehicle 124. The one or more images may be received,for example, in the form of analog and/or digital signals transmittedover the one or more networks 370. Alternatively or additionally, theimage analysis system 320 may receive at least one of the one or moreimages via a physical medium. For example, a USB storage device mayphysically transfer data from the inspection device 350 to the imageanalysis system 350. In any case, the image analysis system 320 maystore the one or more images at a data storage 330 (e.g., one or morememories and/or servers) and/or at the one or more program memories 322.

The image analysis system 320 may employ various image processingtechniques, algorithms, calculations, etc. in analyzing the one or moreimages of the vehicle 124. For example, the image analysis system 320may utilize pixilation, linear filtering, image editing, imagerestoration, principal component analysis, independent componentanalysis, hidden Markov models, anisotropic diffusion, partialdifferential equations, self-organizing maps, neural networks, wavelets,and/or other techniques, algorithms, and/or calculations.

The image analysis system 320 may analyze, via the one or moreprocessors 326, the one or more images of the vehicle 124 based upondata (e.g., stored at the data storage 330 or in the one or more programmemories 322) indicative of at least one of vehicle damage or a vehicledefect being shown in the one or more images. The data indicative of thevehicle damage and/or the vehicle defect being shown in the one or moreimages may include, for instance, data indicative of one or more imagecharacteristics that correspond to a presence of damage and/or adefect(s); image data representative of other (e.g., previouslycaptured) images showing vehicle damage and/or a vehicle defect(s);and/or any other suitable data. Based upon the analyzing of the one ormore images, the image analysis system 320 may identify, via the one ormore processors 326, the at least one of the damage to the vehicle 124or the defect of the vehicle 124.

In some aspects, analyzing the one or more images of the vehicle 124 mayinclude (i) comparing the one or more images of at least a portion ofthe vehicle 124 to one or more reference images of vehicle damagesand/or vehicle defects of one or more reference vehicles, and (ii)determining a similarity between at least one of the one or more imagesof the vehicle 124 and at least one of the one or more reference images.Identifying the damage to the vehicle 124 and/or the defect of thevehicle 124 may include identifying the damage and/or defect based upona known damage or known defect of a reference vehicle depicted in atleast one of the one or more reference images. For example, the one ormore reference images may include an image I known to depict a brokenvehicle window, and upon comparing the one or more images of the vehicle124 to the reference images, similarity may be determined to existbetween an image X of the one or more images of the vehicle 124 and theimage I. Thus, the vehicle 124 may be identified to have a broken windowbased upon the similarity and the known damage depicted in the image I.

The system 300 may perform additional or alternative actions, includingthe actions described herein. For instance, in some aspects, the system300 may be configured to perform additional actions based upon theidentified damage to the vehicle 124 and/or defect of the vehicle 124.These actions may provide benefits including expedited correction of thedamage/defect, more reliable correction of the damage/defect, and/orreduced cost of labor, and may be performed, for example, by the imageanalysis system 320.

In some aspects, the damage and/or defect of the vehicle 124 may includea damaged vehicle part or a defective vehicle part (e.g., a physicallydamaged or a defective wheel). In these aspects, the system 300 may beconfigured to cause a maintenance, repair, or part replacement to bescheduled for the damaged or defective vehicle part. Further, the system300 may be configured to cause a proper replacement part (i.e., thecorrect part type, size, specification, and/or brand) to be identified.Furthermore, the system 300 may be configured to cause an order for thereplacement part to be initiated. For instance, the image analysissystem 320 may determine a suitable repair facility based upon theidentification of the damaged or defective vehicle part and/or basedupon stored data (e.g., in the data storage 330) regarding one or morerepair facilities, and may cause a request to be sent via the one ormore networks 370 to the determined repair facility to schedule anappointment for the maintenance, repair, or part replacement.

In other aspects, the damage to the vehicle 124 and/or defect of thevehicle 124 may include an improper wheel alignment. In these aspects,the image analysis system 320 may cause a maintenance for correcting theimproper wheel alignment to be scheduled. For instance, the imageanalysis 320 may identify a suitable facility to be identified, and maycause a request to be sent, via the one or more networks 370, to thedetermined facility to schedule an appointment for the correction of theimproper wheel alignment.

In any case, when at least one of damage to the vehicle 124 and/or adefect of the vehicle 124 is identified, the system 300 may beconfigured to estimate a monetary cost of a maintenance, service, and/orrepair for correcting the identified vehicle damage or vehicle defect.Further, the system 300 may be configured to estimate a timeframe forcorrection of the identified vehicle damage or defect of the vehicle.For instance, the image analysis system 320 may estimate, based uponstored data (e.g., in the data storage 330), a monetary cost based upona cost of one or more vehicle replacements and/or an estimated cost ofrepair or service labor. Additionally or alternatively, the imageanalysis 320 may cause a request to be sent, via the one or morenetworks 370, to a determined maintenance, service, and/or repairfacility, the request inquiring as to a monetary cost of a maintenance,repair, and/or service.

If at least one of a damage to the vehicle 124 and/or a defect of thevehicle 124 is identified, the system 300 may further be configured totransmit, to the mobile device 380 (e.g., a smartphone, pager, PDA,smart wearable device, etc.) of a party associated with the vehicle 124,an indication of the identified at least one of the damage or defect.The party associated with the vehicle 124 may include, for example, anowner of the vehicle 124, a lessee of the vehicle 124, a driver of thevehicle 124, and/or an insurance representative (e.g., an automotiveinsurance agent, estimator, underwriter, etc.). The indication of theidentified damage and/or defect may include at least one of a textualexplanation of the identified at least one of the damage and/or defect,one or more images of the identified damage and/or defect, an estimatedmonetary cost for correcting the identified damage and/or defect, or anestimated time frame for correcting the identified damage and/or defect.The indication may be presented at the mobile device 380 in the form ofa text message, a push notification, a web page, a voice message, and/oranother suitable mode.

In some aspects, the system 300 may be further configured to generateand/or modify terms of an insurance policy. For example, in someaspects, the system 300 may be configured to generate one or more termsof an insurance policy based upon the identified at least one of thedamage to the vehicle 124 or defect of the vehicle 124. Additionally oralternatively, the system 300 may be configured to modify one or moreterms of an insurance policy of a party (e.g., an owner or driver)associated with the vehicle. Generated or modified terms of an insurancepolicy may include a premium, a coverage limit, and/or a deductible, forinstance. The insurance policy may be an automotive insurance policy oranother type of policy (e.g., home, life, renters, etc.)

Furthermore, in some aspects, the system 300 may be configured to verifya claim (e.g., a vehicle insurance claim). In one aspect, the system 300may be configured to receive an indication of an insurance claimassociated with a reported at least one of a damage to the vehicle 124or a defect of the vehicle 124. The system 300 may receive theindication, for instance, from an insurance provider and/or from aninsured party via the mobile device 380 or via another suitablecomputing device. The system 300 may further be configured to receiveone or more images captured by the imaging unit 352 of the inspectiondevice 350 that is at least one of autonomously operated orremotely-controlled, the one or more images being of at least a portionof the vehicle 124. The system 300 may receive the one or more images,for instance, from an insurance provider and/or from an insured partyvia the mobile device 380 or via another suitable computing device. Thesystem 300 may further be configured to analyze one or more images toidentify at least one of damage to the vehicle 124 or a defect of thevehicle 124, and analyze the identified at least one of the damage tothe vehicle 124 or the defect of the vehicle 124 with respect to thereported damage and/or defect to determine whether the damage to thevehicle 124 has occurred or the reported defect of the vehicle 124 ispresent. If the system 300 determines that the reported damage to thevehicle 124 has occurred or that the reported defect of the vehicle 124is present, the system 300 may process the insurance claim (e.g., issuea replacement vehicle and/or a payment to an insured party).

In some aspects, the system 300 may be configured to employ machine orcognitive learning techniques, as will be described herein.

Example System Use Scenarios

Use of remotely-controlled and/or autonomously operated imaging-enabledinspection devices (e.g., the inspection device 350) may utilizetechnologies and provide advantages including those advantages that willbe evident from the exemplary use scenarios depicted in FIGS. 4a -4 b.

FIGS. 4a-4b depict profile and aerial views 410 and 450, respectively,of various elements of the system 300 of FIG. 3. In particular, each ofthe profile view 410 of FIG. 4a and the aerial view 450 of FIG. 4bdepict the vehicle 124 inspected by an exemplary ground inspectiondevice 350 a and an example airborne inspection device 350 b. It shouldbe appreciated in light of the teaching and disclosure herein that eachof the example ground inspection devices 350 a and airborne inspectiondevices 350 b may be a suitable implementation of the inspection device350. In the examples of FIGS. 4a and 4b , each ground inspection device350 a may be a remotely-controlled and/or autonomously operated groundinspection device (e.g., an inspection device situated on the ground butstill capable of moving across land, such as an RC car). Each airborneinspection device 350 b may be a remotely-controlled and/or autonomouslyoperated airborne inspection device (e.g., situated in the air andcapable of sustained flight, such as a drone or nano drone). However,other inspection devices are possible. Further, while two inspectiondevices 350 are depicted in each of FIGS. 4a and 4b , additional orfewer inspection devices may be used. In other words, in someembodiments, vehicle inspection may be accomplished using a singleground inspection device 350 a or a single airborne inspection device350 b. In other embodiments, vehicle inspection may utilize two or moreinspection devices 350, which may include a combination of groundinspection devices 350 a and airborne inspection devices 350 b.

Advantages of the use of the ground inspection device 350 a for vehicleinspection will be evident from the profile view 410 of FIG. 4a . Forexample, if the inspection device 350 a is an inspection device of shortheight, it may be possible for the inspection device 350 a to maneuverunder the vehicle 124 to capture images of the undercarriage (includingwheels, axles, and exhaust pipes, for instance) of the vehicle 124.Thus, utilizing the inspection device 350 a, it may not be necessary tomove the vehicle 124 (e.g., from a parking spot in which a mechanic isunable to inspect the vehicle 124) and/or employ a vehicle lift toidentify a damage to the vehicle 124 or defect of the vehicle 124present within the vehicle undercarriage.

Still referring to FIG. 4a , inspection of the vehicle 124 mayadditionally or alternatively utilize the airborne inspection device 350b. The maneuverability of the airborne inspection device 350 b (e.g., adrone or nano drone) may allow the inspection device 350 b to capture avariety of images of at least portions of the vehicle 124, including thefront, sides, rear, and/or roof of the vehicle 124 and the vehicle partsand components included therein.

Referring now to FIG. 4b , an aerial view 450 of the vehicle 124inspected by the inspection devices 350 a and 350 b is depicted. Itshould be appreciated in light of the teaching and disclosure hereinthat, if the ground inspection device 350 a is of sufficiently smallsize, the ground inspection device 350 a may be configured or operatedto maneuver between the vehicle 124 and another nearby vehicle 204 a(which may be, for example, adjacent to the vehicle 124 in a parkinglot) to capture one or more images of at least a portion of the vehicle124. Additionally or alternatively, the airborne inspection device 350 bmay capture one or more images of at least a portion of the vehicle 124,with minimal interference from the adjacent vehicle 204 a.

Specialty imaging technologies, such as specialty lenses in imagingunits 352 a and/or 352 b of the inspection devices 350 a and/or 350 b(where the imaging units 352 a and/or 352 b may be an implementation(s)of the imaging unit 352), respectively, may assist in capturing imagesof the vehicle 124. For example, in some embodiments, an imaging unit352 (e.g., the imaging unit 352 a, the imaging unit 352 b, or anotherimaging unit) of an inspection device 350 (e.g., the ground inspectiondevice 350 a, the airborne inspection device 350 b, or anotherinspection device) may include a wide-angle (e.g., “fisheye”) lens. Ifthe inspection device 350 is positioned sufficiently close to thevehicle 124 (e.g., as the ground inspection device 350 a is depicted inFIGS. 4a and 4b ), a wide-angle lens may allow the imaging unit 352 tocapture a greater portion of the vehicle 124 in a particular image. Ifthe inspection device 350 is positioned farther from the vehicle 124, awide-angle lens may allow the imaging unit 352 to capture an evengreater portion of the vehicle 124 in a single image, and may even allowthe imaging unit 352 to capture useful portions of multiple vehicles ina single image. For instance, if the vehicle 204 a depicted in FIG. 4balso requires inspection, the imaging unit 352 may capture an image ofat least a portion of each of the vehicle 124 and the vehicle 204 asimultaneously.

In other aspects, the imaging unit 352 of the inspection device 350 maybe a 360-degree camera, which may be utilized to capture a greaterportion of the vehicle 124 and/or one or more other vehicles in eachsingle image of one or more images captured by the inspection device350. Still further, in other aspects, the imaging unit 352 of theinspection device 350 may include a zooming lens, the zooming of whichmay be remotely-controlled and/or autonomously operated.

Still further, in other aspects, the imaging unit 352 of the inspectiondevice 350 may additionally or alternatively include other imagingcomponents and/or utilize other imaging protocols. For instance, variouscamera lenses (varying in focal length, aperture, etc.) may be utilizedin the imaging unit 352.

Exemplary Computer-Implemented Method for Identifying Vehicle Damageand/or a Vehicle Defect

FIG. 5 illustrates a flow diagram of an exemplary computer-implementedmethod 500 for identifying at least one or damage to a vehicle (e.g.,the vehicle 124) or a defect of the vehicle 124. The method 500 may beimplemented by the system 300 depicted in FIG. 3 or another suitablesystem. The method 500 may include additional, less, or alternateactions, including actions described with regard to the system 300 ofFIG. 3 and other actions discussed elsewhere herein.

The method 500 may include causing, via at least one of one or moreprocessors (e.g., the one or more processors 326) or one or moretransceivers, one or more sets of imaging data (also referred to hereinas “images”) indicative of at least a portion of the vehicle to becaptured by an imaging unit (e.g., the imaging unit 352) of aninspection device (e.g., the inspection device 350), wherein theinspection device is at least one of autonomously operated orremotely-controlled (block 502). In some aspects, an image analysissystem (e.g., the image analysis system 320) may remotely control theinspection device to capture the one or more images of the vehicle. Inother aspects, the image analysis system may cause the inspection deviceto operate autonomously and/or to capture the one or more images underremote control of another device or party.

The inspection device 350 may be, for example, a ground inspectiondevice (e.g., the ground inspection device 350 a) that is at least oneof autonomously operated or remotely-controlled. Alternatively, theinspection device may be an airborne inspection device (e.g., theairborne inspection device 350 b) that is at least one of autonomouslyoperated or remotely-controlled. Further, multiple inspection devicesmay be utilized to capture the one or more images, and the multipleinspection devices may be a combination of ground and airborneinspection devices.

The imaging unit 352 of the inspection device 350 may include aphotographic camera, a video camera, a lidar imaging unit, a thermalimaging unit, a sonar imaging unit, a radar imaging unit, etc.Accordingly, the one or more images captured by the imaging unit 352 ofthe inspection device 350 may include still photographs, video, or asuitable combination of the two. Further, the one or more images mayinclude photographic images, lidar images, thermal images, radar images,sonar images, or a suitable combination of the above. Further, theimaging unit 352 may utilize specialty lenses such as wide-angle (e.g.,“fisheye”) lenses, 360-degree lenses, zooming lenses, etc.

The method 500 may also include receiving, via at least one of the oneor more processors 326 or the one or more transceivers, the one or moreimages of the at least the portion of the vehicle 124 captured by theimaging unit 352 of the inspection device 350, such as via wirelesscommunication or data transmission over one or more radio frequencylinks or digital communication channels (block 504). Additionally oralternatively, the one or more images may be received via a transfer ofphysical medium (e.g., a USB drive).

The method 500 may also include analyzing, via the one or moreprocessors 326, the one or more images based upon data indicative of atleast one of vehicle damage or a vehicle defect being shown in the oneor more images (block 506). In one aspect, the data indicative of thevehicle damage and/or the vehicle defect being shown in the one or moreimages may include data indicative of one or more image characteristicsthat correspond to a presence of damage and/or a defect(s); image datarepresentative of other (e.g., previously captured) images showingvehicle damage and/or a vehicle defect(s); and/or any other suitabledata.

In some aspects, analyzing the one or more images may include comparing,via the one or more processors 326, the one or more images to one ormore reference images of at least one of vehicle damages or vehicledefects of one or more reference vehicles. Analyzing the one or moreimages may further include determining, via the one or more processors326, a similarity between at least one of the one or more images and atleast one of the one or more reference images. Identification of the atleast one of the damage to the vehicle 124 or the defect of the vehicle124 may be based upon at least one of a known damage or a known defectof one of the one or more reference vehicles depicted in the at leastone of the one or more reference images.

The method 500 may also include identifying, via the one or moreprocessors 326, the at least one of the damage to the vehicle 124 or thedefect of the vehicle 124 based upon the analyzing of the one or moreimages (block 508).

In some aspects, the identified at least one of the damage or the defectmay include at least one of a damaged vehicle part or a defectivevehicle part. In these aspects, the method 500 may further includescheduling, via the one or more processors 326, at least one of amaintenance, a repair, or a replacement of the at least one of thedamaged vehicle part or the defective vehicle part. The method 500 mayfurther include identifying, via the one or more processors 326, areplacement part for replacing the at least one of the damaged vehiclepart or the defective vehicle part. The method 500 may further includeinitiating, via the one or more processors 326, an order of thereplacement part for replacing the at least one of the damaged vehiclepart or the defective vehicle part.

Additionally or alternatively, in some aspects, the identified at leastone of the damage or the defect may include an improper wheel alignment.In these aspects, the method 500 may further include scheduling, via theone or more processors 326, a maintenance for correcting the improperwheel alignment.

In some aspects, the identified damage to the vehicle or defect of thevehicle may be utilized for insurance purposes. For instance, the method500 may further include generating, via the one or more processors, oneor more terms of an insurance policy (e.g., an insurance policy of anowner or driver of the vehicle) based upon the identified at least oneof the damage or the defect. Additionally or alternatively, the method500 may include modifying, via the one or more processors, based uponthe identified at least one of the damage or the defect, an insurancepolicy of a party (e.g., an owner or driver) associated with the vehicle124. Generated or modified terms of an insurance policy may include apremium, a coverage limit, and/or a deductible, for instance. Theinsurance policy may be an automotive insurance policy or another typeof insurance policy (e.g., home, life, renters, etc.)

Further, in some aspects, the method 500 may include estimating, via theone or more processors 326, a monetary cost of at least one of amaintenance, a service, or a repair for correcting the identified atleast one of the damage or the defect.

Furthermore, in some aspects, the method 500 may include transmitting,via at least one of the one or more processors 326 or the one or moretransceivers, to at least one of a mobile device (e.g., the mobiledevice 380) of an owner and/or driver of the vehicle 124 or a mobiledevice of an insurance representative (e.g., an agent, underwriter,estimator, etc.), an indication of the identified at least one of thedamage or the defect. The indication of the identified damage and/ordefect may include at least one of a textual explanation of theidentified at least one of the damage or the defect, one or more imagesof the identified damage and/or defect, an estimated monetary cost forcorrecting the identified damage and/or defect, or an estimated timeframe for correcting the identified damage and/or defect. The mobiledevice may be, for example, a smartphone, PDA, smart wearable device,etc., and the indication may be presented at the mobile device in theform of a text message, a push notification, a web page, a voicemessage, and/or another suitable mode.

Exemplary Detecting of Insurance Buildup or Fraud

In some aspects, a remotely-controlled and/or autonomously operatedinspection device (e.g., the inspection device 350) may be utilized todetect insurance buildup or fraud. Generally, one or moreremotely-controlled and/or autonomously operated inspection devices 350may capture one or more images of a vehicle (e.g., the vehicle 124) forwhich an insurance claim (e.g., an automotive insurance claim of adamage or defect associated with the vehicle 124) has been made, andanalysis of the one or more captured images may result in adetermination of whether the insurance claim matches an identifieddamage to the vehicle 124 or defect of the vehicle 124. If the claimeddamage and/or defect generally matches the damage and/or defectidentified from the one of more images, the claim may be verified andprocessed. If the claimed damage and/or defect does not match theidentified damage and/or defect (for example, if the claimed damageand/or defect is not identified, or the claimed damage and/or defectexceeds the identified damage and/or defect), it may be determined thata claimant (e.g., an owner of an insurance policy and/or the vehicle)committed insurance buildup or fraud. Additionally or alternatively, itmay be determined that an automotive repair, maintenance, or serviceshop committed fraud or buildup in identifying the damage and/or defectof the vehicle 124.

FIG. 6 illustrates a flow diagram of an exemplary computer-implementedmethod 600 for verifying a claim (e.g., a vehicle insurance claim asdescribed herein, though other claims are possible). The method 600 maybe implemented by the system 300 depicted in FIG. 3 or another suitablesystem. The method 600 may include additional, less, or alternateactions, including actions discussed elsewhere herein.

The method 600 may include receiving, via at least one of one or moreprocessors (e.g., the one or more processors 326) or one or moretransceivers (such as via wireless communication or data transmissionover one or more radio frequency links or digital communicationchannels), an indication of a vehicle insurance claim associated with areported at least one of a damage to a vehicle (e.g., the vehicle 124)or a defect of the vehicle 124 (block 602). The vehicle insurance claimmay be made, for instance, by an owner of the vehicle 124, a driver ofthe vehicle 124, or an insurance representative (e.g., an automotiveinsurance agent) operating on behalf of the owner and/or driver. Theindication of the claim may be received over a computer communicationnetwork (e.g., the one or more networks 370) using known technologiesand protocols.

The method 600 may also include receiving, via at least one of the oneor more processors 326 or one or more transceivers (such as via wirelesscommunication or data transmission over one or more radio frequencylinks or digital communication channels), one or more sets of imagingdata (also referred to herein as “images”) captured by an imaging unit(e.g., the imaging unit 352) of an inspection device (e.g., theinspection device 350) that is at least one of autonomously operated orremotely-controlled, the one or more images being of at least a portionof the vehicle 124 (block 604). Additionally or alternatively, the oneor more images may be received via a physical medium (e.g., a USBdrive). Receiving the one or more images may occur, for instance, inresponse to receiving the indication of the insurance claim.

The inspection device may be, for example, a ground inspection device(e.g., the ground inspection device 350 a) that is at least one ofautonomously operated or remotely-controlled. Alternatively, theinspection device may be an airborne inspection device (e.g., theairborne inspection device 350 b) that is at least one of autonomouslyoperated or remotely-controlled. Further, multiple inspection devices350 may be utilized to capture the one or more images, and the multipleinspection devices 350 may be a combination of ground and airborneinspection devices.

The imaging unit 352 of the inspection device 350 may include aphotographic camera, a video camera, a lidar imaging unit, a thermalimaging unit, a sonar imaging unit, a radar imaging unit, etc.Accordingly, the one or more images captured by the imaging unit 352 ofthe inspection device 250 may include still photographs, video, or asuitable combination of the two. Further, the one or more images mayinclude photographic images, lidar images, thermal images, radar images,sonar images, or a suitable combination of the above. Further, theimaging unit 352 may utilize specialty lenses such as wide-angle (e.g.,“fisheye”) lenses, 360-degree lenses, zooming lenses, etc.

In some aspects, the inspection device 350 may operate according to thereceived insurance claim. For instance, if the received insurance claimdescribes damage only to the front bumper of the vehicle, the inspectiondevice 350 may be controlled or autonomously operated to capture one ormore images only of portions of the front bumper and surroundingportions of the vehicle 124. However, the inspection device 350 mayadditionally capture one or more images of parts of other parts of thevehicle 124 not described in the insurance claim, in order to ensure,for example, that all damages to the vehicle 124 or defects of thevehicle 124 may be identified and corrected. In other aspects, however,the inspection device 350 may capture one or more images of the vehicle124 before an insurance claim is received.

The method 600 may also include analyzing, via the one or moreprocessors 326, the one or more images to identify at least one ofdamage to the vehicle 124 or a defect of the vehicle 124 (block 606).

In some aspects, analyzing the one or more images may include comparing,via the one or more processors 326, the one or more images to one ormore reference images of at least one of vehicle damages or vehicledefects of one or more reference vehicles. Analyzing the one or moreimages may further include determining, via the one or more processors326, a similarity between at least one of the one or more images and atleast one of the one or more reference images. Identification of the atleast one of the damage to the vehicle 124 or the defect of the vehicle124 may be based upon at least one of a known damage or a known defectof one of the one or more reference vehicles depicted in the at leastone of the one or more reference images.

The method 600 may also include analyzing, via the one or moreprocessors 326, the identified at least one of the damage to the vehicleor the defect of the vehicle with respect to the reported damage todetermine whether the damage to the vehicle has occurred or the reporteddefect of the vehicle is present (block 608). Effective, the result ofthis action may include a determination of one or more of (1) that theidentified damage or defect generally aligns with the reported damage ordefect, indicating a legitimate insurance claim, (2) that the reporteddamage or defect exceeds the identified damage or defect (in number ofdamages/defects and/or in severity of damages/defects), suggesting somedegree of buildup or fraud by the claimant in the insurance claim,and/or (3) that the reported damage or defect substantially fails toalign with the identified damage or defect, indicating substantial fraudpresent in the insurance claim.

The method 600 may also include processing, via the one or moreprocessors 326, the insurance claim when it is determined that thereported damage to the vehicle 124 has occurred or that the reporteddefect of the vehicle 124 is present (block 610). Processing theinsurance claim may include issuing a replacement vehicle, issuing amonetary compensation to an owner of the automotive insurance policyassociated with the insurance claim, etc.

In some aspects, the identified at least one of the damage or the defectmay include at least one of a damaged vehicle part or a defectivevehicle part. In these aspects, the method 600 may further includescheduling, via the one or more processors 326, at least one of amaintenance, a repair, or a replacement of the at least one of thedamaged vehicle part or the defective vehicle part. The method 600 mayfurther include identifying, via the one or more processors 326, areplacement part for replacing the at least one of the damaged vehiclepart or the defective vehicle part. The method 600 may further includeinitiating, via the one or more processors 326, an order of thereplacement part for replacing the at least one of the damaged vehiclepart or the defective vehicle part.

Additionally or alternatively, in some aspects, the identified at leastone of the damage or the defect may include an improper wheel alignment.In these aspects, the method 600 may further include scheduling, via theone or more processors 326, a maintenance for correcting the improperwheel alignment.

In some aspects, the identified damage to the vehicle or defect of thevehicle may be utilized to generate and/or modify terms of an insurancepolicy. For instance, the method 600 may further include generating, viathe one or more processors 326, one or more terms of an insurance policy(e.g., an insurance policy of an owner or driver of the vehicle) basedupon the identified at least one of the damage or the defect.Additionally or alternatively, the method 600 may include modifying, viathe one or more processors 326, based upon the identified at least oneof the damage or the defect, an insurance policy of a party (e.g., anowner or driver) associated with the vehicle 124. Generated or modifiedterms of an insurance policy may include a premium, a coverage limit,and/or a deductible, for instance. The insurance policy may be anautomotive insurance policy or another type of insurance policy (e.g.,home, life, renters, etc.). The generated terms of the insurance policyand/or the modification of the insurance policy may further be basedupon the determined veracity of the insurance claim.

Further, in some aspects, the method 600 may include estimating, via theone or more processors 326, a monetary cost of at least one of amaintenance, a service, or a repair for correcting the identified atleast one of the damage or the defect.

Furthermore, in some aspects, the method 600 may include transmitting,via at least one of the one or more processors 326 or the one or moretransceivers, to at least one of a mobile device (e.g., the mobiledevice 380) of an owner of the vehicle 124 and/or driver of the vehicle124 or a mobile device of an insurance representative (e.g., an agent,underwriter, estimator, etc.), an indication of the identified at leastone of the damage or the defect. The indication of the identified damageand/or defect may include at least one of a textual explanation of theidentified at least one of the damage or the defect, one or more imagesof the identified damage and/or defect, an estimated monetary cost forcorrecting the identified damage and/or defect, or an estimated timeframe for correcting the identified damage and/or defect. The mobiledevice may be, for example, a smartphone, PDA, smart wearable device,etc., and the indication may be presented at the mobile device in theform of a text message, a push notification, a web page, a voicemessage, and/or another suitable mode.

Exemplary Use of Machine Learning in Identifying Vehicle Damage and/orDefects

The present aspects may also employ cognitive computing and/orpredictive modeling techniques, including machine learning techniques oralgorithms. For instance, training sets of imaging data (also referredto herein as “images”) indicative of at least portions of referencevehicles may be input into machine learning programs which may betrained to identify damages and/or defects in vehicles. Systems mayutilize these trained programs to (i) identify and/or schedulemaintenances, repairs, part replacements and/or services for correctingdamages and/or defects, (ii) identify replacement parts for correctingvehicle damages and/or defects, (iii) generating or modifying insurancepolicies and terms therein, (iv) estimate monetary costs and/or timerequirements for correcting vehicle damages and/or defects, and/or (v)transmit indications of vehicle damages and/or defects to mobiledevices.

In certain aspects, the cognitive computing and/or predictive modelingtechniques discussed herein may include heuristic engines or algorithms,machine learning, cognitive learning, deep learning, combined learning,and/or pattern recognition techniques. For instance, a processor or aprocessing element may be trained using supervised or unsupervisedmachine learning, and the machine learning program may employ a neuralnetwork, which may be a convolutional neural network, a deep learningneural network, or a combined learning module or program that learns intwo or more fields or areas of interest. Machine learning may involveidentifying and recognizing patterns in existing images of damages ofvehicles and/or defects of vehicles in order to facilitate makingpredictions for subsequent images of subsequent vehicles. Models may becreated based upon example inputs in order to make valid and reliablepredictions for novel inputs.

Additionally or alternatively, the machine learning programs may betrained by inputting sample images of vehicle damages and/or defectsinto the programs. The machine learning programs may utilize deeplearning algorithms that may be primarily focused on patternrecognition, and/or may be trained after processing multiple examples.The machine learning programs may include Bayesian program learning(BPL), pattern recognition and synthesis, image or object recognition,optical character recognition, and/or natural language processing—eitherindividually or in combination. The machine learning programs may alsoinclude natural language processing, semantic analysis, and/or automaticreasoning.

In supervised machine learning, a processing element may be providedwith example inputs and their associated outputs, and may seek todiscover a general rule that maps inputs to outputs, so that whensubsequent novel inputs are provided the processing element may, basedupon the discovered rule, accurately predict the correct output. Inunsupervised machine learning, the processing element may be required tofind its own structure in unlabeled example inputs. In one aspect,machine learning techniques may be used to identify damage to a vehicleor a defect of a vehicle based upon one or more images of at least aportion of the vehicle, the one or more images captured by an imagingunit of an inspection device (e.g., a grounded or aerial,remotely-controlled and/or autonomously operated device).

In one aspect, a processing element (and/or heuristic engine oralgorithm discussed herein) may be trained by providing it with a largesample of reference images of at least a portion of known referencevehicles, the known reference vehicles having known damages and/ordefects. Based upon these analyses, the processing element may learn howto identify characteristics and patterns that may then be applied toanalyzing one or more images of a current vehicle (also referred toherein as a “present vehicle”) to identify one or more damages and/orone of more defects of the present vehicle.

FIG. 7 depicts an exemplary computer-implemented method 700 foridentifying at least one of damage to a present vehicle (e.g., thevehicle 124) or a defect of the present vehicle 124 based upon trainingimages indicative of reference vehicles. The method 700 may beimplemented by the system 300 depicted in FIG. 3 or another suitablesystem. The method 700 may include additional, less, or alternateactions, including actions discussed elsewhere herein.

The method 700 may include training one or more processing elements(e.g., the one or more processors 326) to identify at least one ofvehicle damages or vehicle defects based upon the training images, thetraining images being images of, for each of the reference vehicles, atleast a portion of the reference vehicle (block 702). The trainingimages may be captured by a remotely-controlled and/or autonomouslyoperating inspection device (e.g., the inspection device 350).Additionally or alternatively, the training images may be captured inanother suitable manner. The training images may include stillphotographs, video, or some combination of the two. Further, thetraining images may include photographic images, lidar images, thermalimages, radar images, sonar images, or a suitable combination of theabove.

The method 700 may also include receiving, via a communication element(e.g., the one or more network interfaces 360 and/or the one or morenetworks 370, and via wireless communication or data transmission overone or more radio frequency links or digital communication channels),one or more present images captured by an imaging unit (e.g., theimaging unit 352) of the inspection device 350 that is at least one ofautonomously operated or remotely-controlled, each of the one or morepresent images being of at least a portion of the present vehicle 124(block 704). Additionally or alternatively, the one or more presentimages may be received via a physical medium (e.g., a USB drive).

The inspection device 350 may be, for example, a ground inspectiondevice (e.g., the ground inspection device 350 a) that is at least oneof autonomously operated or remotely-controlled. Alternatively, theinspection device 350 may be an airborne inspection device (e.g., theairborne inspection device 350 b) that is at least one of autonomouslyoperated or remotely-controlled. Further, multiple inspection devices350 may be utilized to capture the one or more images, and the multipleinspection devices 350 may be a combination of ground and airborneinspection devices.

The imaging unit 352 of the inspection device 350 may include aphotographic camera, a video camera, a lidar imaging unit, a thermalimaging unit, a sonar imaging unit, a radar imaging unit, etc.Accordingly, the one or more images captured by the imaging unit 352 ofthe inspection device 350 may include still photographs, video, or asuitable combination of the two. Further, the one or more images mayinclude photographic images, lidar images, thermal images, radar images,sonar images, or a suitable combination of the above. Further, theimaging unit 352 may utilize specialty lenses such as wide-angle (e.g.,“fisheye”) lenses, 360-degree lenses, zooming lenses, etc.

The method 700 may also include analyzing, via the one or more trainedprocessing elements 326, the one or more present images to identify theat least one of the damage to the present vehicle 124 or the defect ofthe present vehicle 124 (block 706).

In some aspects, the identified at least one of the damage or the defectmay include at least one of a damaged vehicle part or a defectivevehicle part. In these aspects, the method 700 may further includescheduling, via the one or more processing elements 326, at least one ofa maintenance, a repair, or a replacement of the at least one of thedamaged vehicle part or the defective vehicle part. The method 700 mayfurther include identifying, via the one or more processing elements326, a replacement part for replacing the at least one of the damagedvehicle part or the defective vehicle part. The method 700 may furtherinclude initiating, via the one or more processing elements 326, anorder of the replacement part for replacing the at least one of thedamaged vehicle part or the defective vehicle part.

Additionally or alternatively, in some aspects, the identified at leastone of the damage or the defect may include an improper wheel alignment.In these aspects, the method 700 may further include scheduling, via theone or more processing elements 326, a maintenance for correcting theimproper wheel alignment.

In some aspects, the identified damage to the vehicle 124 or defect ofthe vehicle 124 may be utilized for insurance purposes. For instance,the method 700 may further include generating, via the one or moreprocessing elements 326, one or more terms of an insurance policy (e.g.,an insurance policy of an owner or driver of the vehicle 124) based uponthe identified at least one of the damage or the defect. Additionally oralternatively, the method 700 may include modifying, via the one or moreprocessing elements 326, based upon the identified at least one of thedamage or the defect, an insurance policy of a party (e.g., an owner ordriver) associated with the vehicle 124. Generated or modified terms ofan insurance policy may include a premium, a coverage limit, and/or adeductible, for instance. The insurance policy may be an automotiveinsurance policy or another type of insurance policy (e.g., home, life,renters, etc.).

Further, in some aspects, the method 700 may include estimating, via theone or more processing elements 326, a monetary cost of at least one ofa maintenance, a service, or a repair for correcting the identified atleast one of the damage or the defect.

Furthermore, in some aspects, the method 700 may include transmitting,via at least one of the one or more processing elements 326 or thecommunication element 370 and/or 360, to at least one of a mobile device(e.g., the mobile device 380) of an owner and/or driver of the presentvehicle 124 or a mobile device of an insurance representative (e.g., anagent, underwriter, estimator, etc.), an indication of the identified atleast one of the damage or the defect. The indication of the identifieddamage and/or defect may include at least one of a textual explanationof the identified at least one of the damage or the defect, one or moreimages of the identified damage and/or defect, an estimated monetarycost for correcting the identified damage and/or defect, or an estimatedtime frame for correcting the identified damage and/or defect. Themobile device may be, for example, a smartphone, PDA, smart wearabledevice, etc., and the indication may be presented at the mobile devicein the form of a text message, a push notification, a web page, a voicemessage, and/or another suitable mode.

Exemplary Computer System Configured to Identify Damage to a Vehicle ora Defect of the Vehicle

As depicted by, and discussed in relation to, FIGS. 1-7, for example, inone aspect, a computer system configured to use identify at least one ofdamage to a vehicle or a defect of the vehicle may be provided. Thecomputer system may include at least one of one or more processors orone or more associated transceivers. The at least one of the one or moreprocessors and/or the one or more associated transceivers may beconfigured to: (1) cause one or more sets of imaging data (also referredto herein as “images”) indicative of at least a portion of the vehicleto be captured by an imaging unit of an inspection device, wherein theinspection device is at least one of autonomously operated orremotely-controlled; (2) receive the one or more images of the at leastthe portion of the vehicle captured by the imaging unit of theinspection device (such as via wireless communication or datatransmission over one or more radio frequency links or digitalcommunication channels); (3) analyze the one or more images based upondata indicative of at least one of vehicle damage or a vehicle defectbeing shown in the one or more images; and/or (4) identify the at leastone of the damage to the vehicle or the defect of the vehicle based uponthe analyzing of the one or more images. The computer system may performadditional, fewer, or alternate actions, including actions described inthis detailed description.

To analyze the one or more images, the at least one of the one or moreprocessors and/or the one or more associated transceivers may beconfigured to (1) compare the one or more images to one or morereference images of at least one of vehicle damages or vehicle defectsof one or more reference vehicles; and/or (2) determine, via the one ormore processors, a similarity between at least one of the one or moreimages and at least one of the one or more reference images, whereinidentifying the at least one of the damage to the vehicle or the defectof the vehicle includes identifying the at least one of the damage tothe vehicle or the defect of the vehicle based upon at least one of aknown damage or a known defect of one of the one or more referencevehicles depicted in the at least one of the one or more referenceimages.

Additionally or alternatively, if the identified at least one of thedamage or the defect includes at least one of a damaged vehicle part ora defective vehicle part, the at least one of the one or more processorsand/or the one or more associated transceivers may be configured to (1)schedule at least one of a maintenance, a repair, or a replacement ofthe at least one of the damaged vehicle part or the defective vehiclepart; (2) identify a replacement part for replacing the at least one ofthe damaged vehicle part or the defective vehicle part; and/or (3)initiate an order of the replacement part for replacing the at least oneof the damaged vehicle part or the defective vehicle part.

Additionally or alternatively, if the identified at least one of thedamage or the defect includes an improper wheel alignment, the at leastone of the one or more processors and/or the one or more associatedtransceivers may be configured to schedule a maintenance for correctingthe improper wheel alignment.

Additionally or alternatively, the at least one of the one or moreprocessors and/or the one or more associated transceivers may beconfigured to (1) generate one or more terms of an insurance policy(e.g., a premium, coverage limit, deductible, etc.) based upon theidentified at least one of the damage or the defect; and/or (2) modify,based upon the identified at least one of the damage or the defect, aninsurance policy of a party associated with the vehicle.

Additionally or alternatively, the at least one of the one or moreprocessors and/or the one or more associated transceivers may beconfigured to estimate a monetary cost of at least one of a maintenance,a service, or a repair for correcting the identified at least one of thedamage or the defect.

Additionally or alternatively, the at least one of the one or moreprocessors and/or the one or more associated transceivers may beconfigured to transmit, to at least one of a mobile device of an ownerof the vehicle or a mobile device of an insurance representative, anindication of the identified at least one of the damage or the defect.

Exemplary Computer System Configured to Verify a Vehicle Insurance Claim

As depicted by, and discussed in relation to, FIGS. 1-7, for example, inone aspect, a computer system configured to verify a claim (e.g., avehicle insurance claim as described herein, though other claims arepossible) may be provided. The computer system may include at least oneof one or more processors or one or more associated transceivers. The atleast one of the one or more processors and/or the one or moreassociated transceivers may be configured to: (1) receive an indicationof an insurance claim associated with a reported at least one of adamage to a vehicle or a defect of the vehicle (such as via wirelesscommunication or data transmission over one or more radio frequencylinks or digital communication channels); (2) receive one or more setsof imaging data (also referred to herein as “images”) captured by animaging unit of an inspection device that is at least one ofautonomously operated or remotely-controlled, the one or more imagesbeing of at least a portion of the vehicle (such as via wirelesscommunication or data transmission over one or more radio frequencylinks or digital communication channels); (3) analyze the one or moreimages to identify at least one of damage to the vehicle or a defect ofthe vehicle; (4) analyze the identified at least one of the damage tothe vehicle or the defect of the vehicle with respect to the reporteddamage to determine whether the damage to the vehicle has occurred orthe reported defect of the vehicle is present; and/or (5) process theinsurance claim when it is determined that the reported damage to thevehicle has occurred or that the reported defect of the vehicle ispresent. The computer system may perform additional, fewer, or alternateactions, including actions described in this detailed description.

To analyze the one or more images, the at least one of the one or moreprocessors and/or the one or more associated transceivers may beconfigured to (1) compare the one or more images to one or morereference images of at least one of vehicle damages or vehicle defectsof one or more reference vehicles; and/or (2) determine, via the one ormore processors, a similarity between at least one of the one or moreimages and at least one of the one or more reference images, whereinidentifying the at least one of the damage to the vehicle or the defectof the vehicle includes identifying the at least one of the damage tothe vehicle or the defect of the vehicle based upon at least one of aknown damage or a known defect of one of the one or more referencevehicles depicted in the at least one of the one or more referenceimages.

Additionally or alternatively, if the identified at least one of thedamage or the defect includes at least one of a damaged vehicle part ora defective vehicle part, the at least one of the one or more processorsand/or the one or more associated transceivers may be configured to (1)schedule at least one of a maintenance, a repair, or a replacement ofthe at least one of the damaged vehicle part or the defective vehiclepart; (2) identify a replacement part for replacing the at least one ofthe damaged vehicle part or the defective vehicle part; and/or (3)initiate an order of the replacement part for replacing the at least oneof the damaged vehicle part or the defective vehicle part.

Additionally or alternatively, if the identified at least one of thedamage or the defect includes an improper wheel alignment, the at leastone of the one or more processors and/or the one or more associatedtransceivers may be configured to schedule a maintenance for correctingthe improper wheel alignment.

Additionally or alternatively, the at least one of the one or moreprocessors and/or the one or more associated transceivers may beconfigured to (1) generate one or more terms of an insurance policy(e.g., a premium, coverage limit, deductible, etc.) based upon theidentified at least one of the damage or the defect; and/or (2) modify,based upon the identified at least one of the damage or the defect, aninsurance policy of a party associated with the vehicle.

Additionally or alternatively, the at least one of the one or moreprocessors and/or the one or more associated transceivers may beconfigured to estimate a monetary cost of at least one of a maintenance,a service, or a repair for correcting the identified at least one of thedamage or the defect.

Additionally or alternatively, the at least one of the one or moreprocessors and/or the one or more associated transceivers may beconfigured to transmit, to at least one of a mobile device of an ownerof the vehicle or a mobile device of an insurance representative, anindication of the identified at least one of the damage or the defect.

Exemplary Computer System Configured to Identify Damage to a PresentVehicle or a Defect of the Present Vehicle

As depicted by, and discussed in relation to, FIGS. 1-7, for example, inone aspect, a computer system configured to use identify at least one ofdamage to a current vehicle (also referred to herein as a “presentvehicle”) or a defect of the present vehicle may be provided. Thecomputer system may include at least one of one or more processingelements or one or more communication elements. The at least one of theone or more processing elements and/or the one or more communicationelements may be configured to: (1) train the one or more processingelements to identify at least one of vehicle damages or vehicle defectsbased upon the training sets of imaging data (also referred to herein as“images”) the training images being images indicative of, for each ofthe reference vehicles, at least a portion of the reference vehicle; (2)receive one or more present images captured by an imaging unit of aninspection device that is at least one of autonomously operated orremotely-controlled, each the one or more present images being of atleast a portion of the present vehicle (such as via wirelesscommunication or data transmission over one or more radio frequencylinks or digital communication channels); and/or (3) analyze the one ormore present images to identify the at least one of the damage to thepresent vehicle or the defect of the present vehicle. The computersystem may perform additional, fewer, or alternate actions, includingactions described in this detailed description.

Additionally or alternatively, if the identified at least one of thedamage or the defect includes at least one of a damaged vehicle part ora defective vehicle part, the at least one of the one or more processingelements and/or the one or more communication elements may be configuredto (1) schedule at least one of a maintenance, a repair, or areplacement of the at least one of the damaged vehicle part or thedefective vehicle part; (2) identify a replacement part for replacingthe at least one of the damaged vehicle part or the defective vehiclepart; and/or (3) initiate an order of the replacement part for replacingthe at least one of the damaged vehicle part or the defective vehiclepart.

Additionally or alternatively, if the identified at least one of thedamage or the defect includes an improper wheel alignment, the at leastone of the one or more processing elements and/or the one or morecommunication elements may be configured to schedule a maintenance forcorrecting the improper wheel alignment.

Additionally or alternatively, the at least one of the one or moreprocessing elements and/or the one or more communication elements may beconfigured to (1) generate one or more terms of an insurance policy(e.g., a premium, coverage limit, deductible, etc.) based upon theidentified at least one of the damage or the defect; and/or (2) modify,based upon the identified at least one of the damage or the defect, aninsurance policy of a party associated with the present vehicle.

Additionally or alternatively, the at least one of the one or moreprocessing elements and/or the one or more communication elements may beconfigured to estimate a monetary cost of at least one of a maintenance,a service, or a repair for correcting the identified at least one of thedamage or the defect.

Additionally or alternatively, the at least one of the one or moreprocessing elements and/or the one or more communication elements may beconfigured to transmit, to at least one of a mobile device of an ownerof the present vehicle or a mobile device of an insurancerepresentative, an indication of the identified at least one of thedamage or the defect.

Exemplary Undercarriage Inspections

In one aspect, a computer-implemented method for identifying damage toan undercarriage of a vehicle or a defect to the undercarriage of thevehicle may be provided. The method may include (1) causing, via one ormore processors or one or more transceivers, imaging data indicative ofat least a portion of an undercarriage of the vehicle to be captured byan imaging unit of an inspection device, wherein the inspection deviceis autonomously operated or remotely-controlled; (2) receiving, via theone or more processors or the one or more transceivers, the imaging dataindicative of the at least the portion of the undercarriage of thevehicle captured by the imaging unit of the inspection device viawireless communication or data transmission over one or more radio linksor digital communication channels; (3) analyzing, via the one or moreprocessors, the imaging data based upon data indicative of undercarriagedamage or an undercarriage defect being indicated by the imaging data;and/or (4) identifying, via the one or more processors, theundercarriage damage or the undercarriage defect based upon theanalyzing of the imaging data to facilitate undercarriage damageidentification and repair. The method may include additional, less, oralternate actions, including those discussed elsewhere herein.

In another aspect, a computer system configured to identifyundercarriage damage or an undercarriage defect of a vehicle may beprovided. The computer system may include one or more processors,servers, sensor, and/or transceivers, and one or more memories storingcomputer-executable instructions that, when executed by the one or moreprocessors, cause the computer system to: (1) cause, via at least one ofthe one or more processors or one or more transceivers, one or more setsof imaging data indicative of at least a portion of an undercarriage ofthe vehicle to be captured by an imaging unit of an inspection device,wherein the inspection device is at least one of autonomously operatedor remotely-controlled; (2) receive, via at least one of the one or moreprocessors or the one or more transceivers, the one or more sets ofimaging data indicative of the at least the portion of the undercarriageof the vehicle captured by the imaging unit of the inspection device;(3) analyze, via the one or more processors, the one or more sets ofimaging data based upon data indicative of at least one of vehicledamage or a vehicle defect being indicated by the one or more sets ofimaging data; and/or (4) identify, via the one or more processors, theat least one of the damage to the vehicle or the defect of the vehiclebased upon the analyzing of the one or more sets of imaging data. Thecomputer system may include additional, less, or alternatefunctionality, including that discussed elsewhere herein.

In another aspect, a computer-implemented method for identifying buildupmay be provided. The method may include (1) receiving, via at least oneof one or more processors or one or more transceivers, an indication ofa claim associated with a reported at least one of undercarriage damageto a vehicle or a defect of the undercarriage of the vehicle; (2)receiving, via at least one of the one or more processors or one or moretransceivers, one or more sets of imaging data captured by an imagingunit of an inspection device that is at least one of autonomouslyoperated or remotely-controlled, the one or more sets of imaging databeing indicative of at least a portion of an undercarriage of thevehicle; (3) analyzing, via the one or more processors, the one or moresets of imaging data to identify at least one of undercarriage damage tothe vehicle or a defect of the undercarriage of the vehicle; (4)analyzing, via the one or more processors, the identified at least oneof the undercarriage damage to the vehicle or the defect of theundercarriage of the vehicle with respect to the reported undercarriagedamage to determine whether the undercarriage damage to the vehicle hasoccurred or the reported defect of the undercarriage of the vehicle ispresent; and/or (5) processing, via the one or more processors, theclaim when it is determined that the reported undercarriage damage tothe vehicle has occurred or that the reported defect of theundercarriage of the vehicle is present. The method may includeadditional, less, or alternate actions, including those discussedelsewhere herein.

In another aspect, a computer system configured to identify buildup maybe provided. The system may include one or more processors, servers,sensors, and/or transceivers; and one or more memories storingcomputer-executable instructions that, when executed by the one or moreprocessors, cause the computer system to: (1) receive, via at least oneof the one or more processors or one or more transceivers, an indicationof a claim associated with a reported at least one of undercarriagedamage or an undercarriage defect associated with the vehicle; (2)receive, via at least one of the one or more processors or one or moretransceivers, one or more sets of imaging data captured by an imagingunit of an inspection device that is at least one of autonomouslyoperated or remotely-controlled, the one or more sets of imaging databeing indicative of at least a portion of the undercarriage of thevehicle; (3) analyze, via the one or more processors, the one or moresets of imaging data to identify at least one of undercarriage damage oran undercarriage defect; (4) analyze, via the one or more processors,the identified at least one of the undercarriage damage or theundercarriage defect with respect to the reported damage to determinewhether the undercarriage damage has occurred or the reportedundercarriage defect is present; and/or (5) process, via the one or moreprocessors, the claim when it is determined that the reportedundercarriage damage to the vehicle has occurred or that the reportedundercarriage defect is present. The computer system may includeadditional, less, or alternate functionality, including that discussedelsewhere herein.

In another aspect, a computer-implemented method for identifying atleast one of undercarriage damage to a current vehicle or anundercarriage defect of the current vehicle damage based upon trainingsets of imaging data indicative of reference vehicles may be provided.The method may include (1) training one or more processing elements toidentify at least one of undercarriage damages or undercarriage defectsbased upon the training sets of imaging data, the training sets ofimaging data being indicative of, for each of the reference vehicles, atleast a portion of an undercarriage of the reference vehicle; (2)receiving, via a communication element (such as via wirelesscommunication or data transmission over one or more radio links ordigital communication channels), one or more current sets of imagingdata captured by an imaging unit of an inspection device that is atleast one of autonomously operated or remotely-controlled, each the oneor more current sets of imaging data being indicative of at least aportion of a undercarriage of the current vehicle; and/or (3) analyzing,via the one or more trained processing elements, the one or more currentsets of imaging data to identify the at least one of the undercarriagedamage to the current vehicle or the undercarriage defect of the currentvehicle. The method may include additional, less, or alternate actions,including those discussed elsewhere herein.

In another aspect, a computer system configured to identify at least oneof undercarriage damage to a current vehicle or an undercarriage defectof the current vehicle based upon training sets of imaging dataindicative of reference vehicles may be provided. The computer systemmay include one or more processing elements; and one or more memoriescomprising computer-executable instructions that, when executed by theone or more processing elements, cause the computer system to (1) trainthe one or more processing elements to identify at least one ofundercarriage damages or undercarriage defects based upon the trainingsets of imaging data, the training sets of imaging data being indicativeof, for each of the reference vehicles, at least a portion of theundercarriage of the reference vehicle; (2) receive, via a communicationelement, one or more current sets of imaging data captured by an imagingunit of an inspection device that is at least one of autonomouslyoperated or remotely-controlled, each the one or more current sets ofimaging data being indicative of at least a portion of an undercarriageof the current vehicle; and/or (3) analyze, via the one or more trainedprocessing elements, the one or more current sets of imaging data toidentify the at least one of the undercarriage damage to the currentvehicle or an undercarriage defect of the current vehicle to facilitateidentification and repair of undercarriage damage. The computer systemmay include additional, less, or alternate functionality, including thatdiscussed elsewhere herein.

Exemplary Embodiments

In one aspect, a computer-implemented method for identifying damage toan undercarriage of a vehicle or a defect to the undercarriage of thevehicle may be provided. The method may include (1) causing, via one ormore processors or one or more transceivers, imaging data indicative ofat least a portion of an undercarriage of the vehicle to be captured byan imaging unit of an inspection device, wherein the inspection deviceis autonomously operated or remotely-controlled; (2) receiving, via theone or more processors or the one or more transceivers, the imaging dataindicative of the at least the portion of the undercarriage of thevehicle captured by the imaging unit of the inspection device viawireless communication or data transmission over one or more radio linksor digital communication channels; (3) analyzing, via the one or moreprocessors, the imaging data based upon data indicative of undercarriagedamage or an undercarriage defect being indicated by the imaging data;and/or (4) identifying, via the one or more processors, theundercarriage damage or the undercarriage defect based upon theanalyzing of the imaging data to facilitate undercarriage damageidentification and repair. The method may include additional, less, oralternate actions, including those discussed elsewhere herein.

For instance, the inspection device may be a ground inspection device orrover that is either autonomously operated or remotely-controlled, orboth. Alternatively, the inspection device may be an airborne inspectiondevice that is either autonomously operated or remotely-controlled, orboth.

The identified undercarriage damage or undercarriage defect may includedamage to the vehicles' drivetrain, wheels, axle, and/or exhaust system.The method may include identifying, via the one or more processors, adamaged or defective undercarriage part associated with the identifiedundercarriage damage or undercarriage defect; and scheduling, via theone or more processors, at least one of a maintenance, a repair, or areplacement of the damaged or defective undercarriage part.

The method may include identifying, via the one or more processors, areplacement part for replacing the damaged or the defectiveundercarriage part. The method may include initiating, via the one ormore processors, an order of the replacement part for replacing thedamaged or defective undercarriage part. The identified undercarriagedamage or undercarriage defect may include an improper wheel alignment.

The method may include scheduling, via the one or more processors, amaintenance for correcting the improper wheel alignment. The imagingdata may include one or more sets of thermal imaging data. The imagingdata may include one or more sets of lidar imaging data. Additionally oralternatively, the imaging data may include one or more sets of imagingdata captured using a wide-angle camera lens of the imaging unit.

The method may include generating or adjusting, via the one or moreprocessors, one or more terms of an insurance policy based upon theidentified undercarriage damage or undercarriage defect. The method mayinclude modifying, via the one or more processors, based upon theidentified undercarriage damage or undercarriage defect, an insurancepolicy of a party associated with the vehicle or covering the vehicle.Modifying the insurance policy may include modifying at least one of apremium, a type of coverage, a coverage limit, discount, or adeductible. Warranties may also be adjusted.

The method may include estimating, via the one or more processors, amonetary cost of at least one of a maintenance, a service, or a repairfor correcting the identified undercarriage damage or undercarriagedefect. The method may include transmitting, via the one or moreprocessors or the one or more transceivers, to at least one of a mobiledevice of an owner of the vehicle or a mobile device of an insurancerepresentative, an indication of the identified undercarriage damage orundercarriage defect via wireless communication or data transmissionover one or more radio frequency links or digital communicationchannels.

Analyzing the imaging data may include (i) comparing, via the one ormore processors, the imaging data to one or more reference sets ofimaging data indicative of at least one of undercarriage damages orundercarriage defects of one or more reference vehicles; and (ii)determining, via the one or more processors, a similarity between theimaging data and at least one of the one or more reference sets ofimaging data, wherein identifying the undercarriage damage or defectincludes identifying the undercarriage damage or defect based upon atleast one of a known damage or a known defect of one of the one or morereference vehicles indicated by the at least one of the one or morereference sets of imaging data.

In another aspect, a computer-implemented method may include (1)receiving, via at least one of one or more processors or one or moretransceivers, an indication of a claim associated with a reported atleast one of undercarriage damage to a vehicle or a defect of theundercarriage of the vehicle; (2) analyzing, via the one or moreprocessors, the one or more sets of imaging data to identify at leastone of undercarriage damage to the vehicle or a defect of theundercarriage of the vehicle; (3) analyzing, via the one or moreprocessors, the identified at least one of the undercarriage damage tothe vehicle or the defect of the undercarriage of the vehicle withrespect to the reported undercarriage damage to determine whether theundercarriage damage to the vehicle has occurred or the reported defectof the undercarriage of the vehicle is present; and/or (4) processing,via the one or more processors, the claim when it is determined that thereported undercarriage damage to the vehicle has occurred or that thereported defect of the undercarriage of the vehicle is present. Themethod may include additional, less, or alternate actions, includingthose discussed elsewhere herein and directly above.

In another aspect, a computer system configured to identifyundercarriage damage or an undercarriage defect of a vehicle may beprovided. The computer system may include one or more processors, andone or more memories storing computer-executable instructions that, whenexecuted by the one or more processors, cause the computer system to:(1) cause, via at least one of the one or more processors or one or moretransceivers, one or more sets of imaging data indicative of at least aportion of an undercarriage of the vehicle to be captured by an imagingunit of an inspection device, wherein the inspection device is at leastone of autonomously operated or remotely-controlled; (2) receive, via atleast one of the one or more processors or the one or more transceivers,the one or more sets of imaging data indicative of the at least theportion of the undercarriage of the vehicle captured by the imaging unitof the inspection device; (3) analyze, via the one or more processors,the one or more sets of imaging data based upon data indicative of atleast one of vehicle damage or a vehicle defect being indicated by theone or more sets of imaging data; and/or (4) identify, via the one ormore processors, the at least one of the damage to the vehicle or thedefect of the vehicle based upon the analyzing of the one or more setsof imaging data. The computer system may include additional, less, oralternate functionality, including that discussed elsewhere herein, suchas that included within the computer-implemented methods detailed above.

In another aspect, a computer system may include one or more processors;and one or more memories storing computer-executable instructions that,when executed by the one or more processors, cause the computer systemto: (1) receive, via at least one of the one or more processors or oneor more transceivers, an indication of a claim associated with areported at least one of undercarriage damage or an undercarriage defectassociated with the vehicle; (2) receive, via at least one of the one ormore processors or one or more transceivers, one or more sets of imagingdata captured by an imaging unit of an inspection device that is atleast one of autonomously operated or remotely-controlled, the one ormore sets of imaging data being indicative of at least a portion of theundercarriage of the vehicle; (3) analyze, via the one or moreprocessors, the one or more sets of imaging data to identify at leastone of undercarriage damage or an undercarriage defect; (4) analyze, viathe one or more processors, the identified at least one of theundercarriage damage or the undercarriage defect with respect to thereported damage to determine whether the undercarriage damage hasoccurred or the reported undercarriage defect is present; and/or (5)process, via the one or more processors, the claim when it is determinedthat the reported undercarriage damage to the vehicle has occurred orthat the reported undercarriage defect is present. The computer systemmay include additional, less, or alternate functionality, including thatdiscussed elsewhere herein.

Additional Considerations

Although the text herein sets forth a detailed description of numerousdifferent aspects, it should be understood that the legal scope of theinvention is defined by the words of the claims set forth at the end ofthis patent. The detailed description is to be construed as exemplaryonly and does not describe every possible aspect, as describing everypossible aspect would be impractical, if not impossible. One couldimplement numerous alternate aspects, using either current technology ortechnology developed after the filing date of this patent, which wouldstill fall within the scope of the claims.

It should also be understood that, unless a term is expressly defined inthis patent using the sentence “As used herein, the term ‘______’ ishereby defined to mean . . . ” or a similar sentence, there is no intentto limit the meaning of that term, either expressly or by implication,beyond its plain or ordinary meaning, and such term should not beinterpreted to be limited in scope based upon any statement made in anysection of this patent (other than the language of the claims). To theextent that any term recited in the claims at the end of this disclosureis referred to in this disclosure in a manner consistent with a singlemeaning, that is done for sake of clarity only so as to not confuse thereader, and it is not intended that such claim term be limited, byimplication or otherwise, to that single meaning. Finally, the patentclaims at the end of this patent application are not intended to beconstrued under 35 U.S.C. § 112(f) unless traditionalmeans-plus-function language is expressly recited, such as “means for”or “step for” language being explicitly recited in the claim(s). Thesystems and methods described herein are directed to an improvement tocomputer functionality, and improve the functioning of conventionalcomputers.

Throughout this specification, plural instances may implementcomponents, operations, or structures described as a single instance.Although individual operations of one or more methods are illustratedand described as separate operations, one or more of the individualoperations may be performed concurrently, and nothing requires that theoperations be performed in the order illustrated. Structures andfunctionality presented as separate components in example configurationsmay be implemented as a combined structure or component. Similarly,structures and functionality presented as a single component may beimplemented as separate components. These and other variations,modifications, additions, and improvements fall within the scope of thesubject matter herein.

Additionally, certain aspects are described herein as including logic ora number of routines, subroutines, applications, or instructions. Thesemay constitute either software (code embodied on a non-transitory,tangible machine-readable medium) or hardware. In hardware, theroutines, etc., are tangible units capable of performing certainoperations and may be configured or arranged in a certain manner. Inexample aspects, one or more computer systems (e.g., a standalone,client or server computer system) or one or more modules of a computersystem (e.g., a processor or a group of processors) may be configured bysoftware (e.g., an application or application portion) as a module thatoperates to perform certain operations as described herein.

In various aspects, a module may be implemented mechanically orelectronically. Accordingly, the term “module” should be understood toencompass a tangible entity, be that an entity that is physicallyconstructed, permanently configured (e.g., hardwired), or temporarilyconfigured (e.g., programmed) to operate in a certain manner or toperform certain operations described herein. Considering aspects inwhich modules are temporarily configured (e.g., programmed), each of themodules need not be configured or instantiated at any one instance intime. For example, where the modules comprise a general-purposeprocessor configured using software, the general-purpose processor maybe configured as respective different modules at different times.Software may accordingly configure a processor, for example, toconstitute a particular module at one instance of time and to constitutea different module at a different instance of time.

Modules can provide information to, and receive information from, othermodules. Accordingly, the described modules may be regarded as beingcommunicatively coupled. Where multiple of such modules existcontemporaneously, communications may be achieved through signaltransmission (e.g., over appropriate circuits and buses) that connectthe modules. In aspects in which multiple modules are configured orinstantiated at different times, communications between such modules maybe achieved, for example, through the storage and retrieval ofinformation in memory structures to which the multiple modules haveaccess. For example, one module may perform an operation and store theoutput of that operation in a memory device to which it iscommunicatively coupled. A further module may then, at a later time,access the memory device to retrieve and process the stored output.Modules may also initiate communications with input or output devices,and can operate on a resource (e.g., a collection of information).

The various operations of example methods described herein may beperformed, at least partially, by one or more processors that aretemporarily configured (e.g., by software) or permanently configured toperform the relevant operations. Whether temporarily or permanentlyconfigured, such processors may constitute processor-implemented modulesthat operate to perform one or more operations or functions. The modulesreferred to herein may, in some example aspects, compriseprocessor-implemented modules.

Similarly, the methods or routines described herein may be at leastpartially processor-implemented. For example, at least some of theoperations of a method may be performed by one or more processors orprocessor-implemented modules. The performance of certain of theoperations may be distributed among the one or more processors, not onlyresiding within a single machine, but deployed across a number ofmachines. In some example aspects, the processor or processors may belocated in a single location, while in other aspects the processors maybe distributed across a number of locations.

The performance of certain of the operations may be distributed amongthe one or more processors, not only residing within a single machine,but deployed across a number of machines. In some example aspects, theone or more processors or processor-implemented modules may be locatedin a single geographic location. In other example aspects, the one ormore processors or processor-implemented modules may be distributedacross a number of geographic locations.

Unless specifically stated otherwise, discussions herein using wordssuch as “processing,” “computing,” “calculating,” “determining,”“presenting,” “displaying,” or the like may refer to actions orprocesses of a machine (e.g., a computer) that manipulates or transformsdata represented as physical (e.g., electronic, magnetic, or optical)quantities within one or more memories (e.g., volatile memory,non-volatile memory, or a combination thereof), registers, or othermachine components that receive, store, transmit, or displayinformation. Some aspects may be described using the expression“coupled” and “connected” along with their derivatives. For example,some aspects may be described using the term “coupled” to indicate thattwo or more elements are in direct physical or electrical contact. Theterm “coupled,” however, may also mean that two or more elements are notin direct contact with each other, but yet still co-operate or interactwith each other. The aspects are not limited in this context.

The terms “insurer,” “insuring party,” and “insurance provider” are usedinterchangeably herein to generally refer to a party or entity (e.g., abusiness or other organizational entity) that provides insuranceproducts, e.g., by offering and issuing insurance policies. Typically,but not necessarily, an insurance provider may be an insurance company.

The terms “insured,” “insured party,” “policyholder,” “customer,”“claimant,” and “potential claimant” are used interchangeably herein torefer to a person, party, or entity (e.g., a business or otherorganizational entity) that is covered by the insurance policy, e.g.,whose insured article or entity (i.e., the vehicle) is covered by thepolicy. A “guarantor,” as used herein, generally refers to a person,party or entity that is responsible for payment of the insurancepremiums. The guarantor may or may not be the same party as the insured,such as in situations when a guarantor has power of attorney for theinsured. An “annuitant,” as referred to herein, generally refers to aperson, party or entity that is entitled to receive benefits from anannuity insurance product offered by the insuring party. The annuitantmay or may not be the same party as the guarantor.

As used herein any reference to “one aspect” or “an aspect” means that aparticular element, feature, structure, or characteristic described inconnection with the aspect may be included in at least one aspect. Theappearances of the phrase “in one aspect” in various places in thespecification are not necessarily all referring to the same aspect. Inaddition, use of the “a” or “an” are employed to describe elements andcomponents of the aspects herein. This is done merely for convenienceand to give a general sense of the description. This description, andthe claims that follow, should be read to include one or at least oneand the singular also includes the plural unless it is obvious that itis meant otherwise.

As used herein, the terms “comprises,” “comprising,” “includes,”“including,” “has,” “having” or any other variation thereof, areintended to cover a non-exclusive inclusion. For example, a process,method, article, or apparatus that comprises a list of elements is notnecessarily limited to only those elements but may include otherelements not expressly listed or inherent to such process, method,article, or apparatus. Further, unless expressly stated to the contrary,“or” refers to an inclusive or and not to an exclusive or. For example,a condition A or B is satisfied by any one of the following: A is true(or present) and B is false (or not present), A is false (or notpresent) and B is true (or present), and both A and B are true (orpresent).

This detailed description is to be construed as exemplary only and doesnot describe every possible aspect, as describing every possible aspectwould be impractical, if not impossible. One could implement numerousalternate aspects, using either current technology or technologydeveloped after the filing date of this application. Upon reading thisdisclosure, those of skill in the art will appreciate still additionalalternative structural and functional designs for system and a methodfor identifying damage to a vehicle or a defect of a vehicle through thedisclosed principles herein. Thus, while particular aspects andapplications have been illustrated and described, it is to be understoodthat the disclosed aspects are not limited to the precise constructionand components disclosed herein. Various modifications, changes andvariations, which will be apparent to those skilled in the art, may bemade in the arrangement, operation and details of the method andapparatus disclosed herein without departing from the spirit and scopedefined in the appended claims.

The particular features, structures, or characteristics of any specificaspect may be combined in any suitable manner and in any suitablecombination with one or more other aspects, including the use ofselected features without corresponding use of other features. Inaddition, many modifications may be made to adapt a particularapplication, situation or material to the essential scope and spirit ofthe present invention. It is to be understood that other variations andmodifications of the aspects of the present invention described andillustrated herein are possible in light of the teachings herein and areto be considered part of the spirit and scope of the present invention.

While the preferred aspects of the invention have been described, itshould be understood that the invention is not so limited andmodifications may be made without departing from the invention. Thescope of the invention is defined by the appended claims, and alldevices that come within the meaning of the claims, either literally orby equivalence, are intended to be embraced therein. It is thereforeintended that the foregoing detailed description be regarded asillustrative rather than limiting, and that it be understood that it isthe claims at the end of this patent, including all equivalents, thatare intended to define the spirit and scope of this invention.

What is claimed is:
 1. A computer-implemented method comprising:analyzing, via one or more processors, one or more sets of imaging datato identify at least one of damage to a vehicle or a defect of thevehicle; analyzing, via the one or more processors, the identified atleast one of the damage to the vehicle or defect of the vehicle withrespect to reported damage indicated in an insurance claim, to determinewhether the reported damage indicated in the insurance claim isaccurate; in response to determining that the reported damage to thevehicle is accurate, processing, via the one or more processors, theinsurance claim; and transmitting, via the one or more processors or viaone or more transceivers, to a mobile device, an indication of theidentified at least one of the damage or the defect.
 2. Thecomputer-implemented method of claim 1, wherein analyzing the one ormore sets of imaging data includes receiving the one or more sets ofimaging data via an autonomously operated inspection device.
 3. Thecomputer-implemented method of claim 1, further comprising scheduling,via the one or more processors, a service to correct the identified atleast one of the damage to the vehicle or defect of the vehicle.
 4. Thecomputer-implemented method of claim 3, wherein scheduling the servicecomprises identifying, based upon the identified at least one of thedamage to the vehicle or defect of the vehicle, a vehicle repairfacility suitable for correcting the identified at least one of thedamage to the vehicle or defect of the vehicle.
 5. Thecomputer-implemented method of claim 4, wherein scheduling the servicefurther comprises transmitting, via the one or more processors, to acomputing system associated with the identified vehicle repair facility,a request to schedule a service to correct the identified at least oneof the damage to the vehicle or defect of the vehicle.
 6. Thecomputer-implemented method of claim 1, further comprising identifying,via the one or more processors, a replacement part for correcting theidentified at least one of the damage to the vehicle or defect of thevehicle.
 7. The computer-implemented method of claim 6, furthercomprising initiating, via the one or more processors, an order of thereplacement part.
 8. The computer-implemented method of claim 1, whereinanalyzing the one or more sets of imaging data includes using one ormore trained processing elements to identify the at least one of damageto a vehicle or a defect of the vehicle, the one or more trainedprocessing elements being trained to identify vehicle damage or vehicledefects based upon training sets of imaging data indicative of damage toreference vehicles or defects of reference vehicles.
 9. A computersystem comprising: one or more processors; and one or more memoriesstoring computer-executable instructions that, when executed by the oneor more processors, cause the computer system to: analyze, via the oneor more processors, one or more sets of imaging data to identify atleast one of damage to a vehicle or a defect of the vehicle; analyze,via the one or more processors, the identified at least one of thedamage to the vehicle or defect of the vehicle with respect to reporteddamage indicated in an insurance claim, to determine whether thereported damage indicated in the insurance claim is accurate; inresponse to determining that the reported damage to the vehicle isaccurate, process, via the one or more processors, the insurance claim;and transmit, via the one or more processors or via one or moretransceivers, to a mobile device, an indication of the identified atleast one of the damage or the defect.
 10. The computer system of claim9, wherein the instructions to analyze the one or more sets of imagingdata include instructions to receive the one or more sets of imagingdata via an autonomously operated inspection device.
 11. The computersystem of claim 9, wherein the non-transitory computer executableinstructions, when executed by the one or more processors, further causethe computer to schedule, via the one or more processors, a service tocorrect the identified at least one of the damage to the vehicle ordefect of the vehicle.
 12. The computer system of claim 11, wherein theinstructions to schedule the service comprise instructions to identify,based upon the identified at least one of the damage to the vehicle ordefect of the vehicle, a vehicle repair facility suitable for correctingthe identified at least one of the damage to the vehicle or defect ofthe vehicle.
 13. The computer system of claim 12, wherein theinstructions to schedule the service further comprise instructions totransmit, via the one or more processors, to a computing systemassociated with the identified vehicle repair facility, a request toschedule a service to correct the identified at least one of the damageto the vehicle or defect of the vehicle.
 14. The computer system ofclaim 9, wherein the non-transitory computer executable instructions,when executed by the one or more processors, further cause the computerto identify, via the one or more processors, a replacement part forcorrecting the identified at least one of the damage to the vehicle ordefect of the vehicle.
 15. The computer system of claim 14, wherein thenon-transitory computer executable instructions, when executed by theone or more processors, further cause the computer to initiate, via theone or more processors, an order of the replacement part.
 16. Thecomputer system of claim 9, wherein the instructions to analyze the oneor more sets of imaging data include instructions to use one or moretrained processing elements to identify the at least one of damage to avehicle or a defect of the vehicle, the one or more trained processingelements being trained to identify vehicle damage or vehicle defectsbased upon training sets of imaging data indicative of damage toreference vehicles or defects of reference vehicles.
 17. One or morenon-transitory computer-readable media storing non-transitorycomputer-readable instructions that, when executed via one or moreprocessors, cause a computer to: analyze, via the one or moreprocessors, one or more sets of imaging data to identify at least one ofdamage to a vehicle or a defect of the vehicle; analyze, via the one ormore processors, the identified at least one of the damage to thevehicle or defect of the vehicle with respect to reported damageindicated in an insurance claim, to determine whether the reporteddamage indicated in the insurance claim is accurate; in response todetermining that the reported damage to the vehicle is accurate,process, via the one or more processors, the insurance claim; andtransmit, via the one or more processors or via one or moretransceivers, to a mobile device, an indication of the identified atleast one of the damage or the defect.
 18. The one or morenon-transitory computer readable media of claim 17, wherein theinstructions to analyze the one or more sets of imaging data includeinstructions to receive the one or more sets of imaging data via anautonomously operated inspection device.
 19. The one or morenon-transitory computer readable media of claim 17, wherein thenon-transitory computer executable instructions, when executed by theone or more processors, further cause the computer to schedule, via theone or more processors, a service to correct the identified at least oneof the damage to the vehicle or defect of the vehicle.
 20. The one ormore non-transitory computer readable media of claim 17, wherein theinstructions to analyze the one or more sets of imaging data includeinstructions to use one or more trained processing elements to identifythe at least one of damage to a vehicle or a defect of the vehicle, theone or more trained processing elements being trained to identifyvehicle damage or vehicle defects based upon training sets of imagingdata indicative of damage to reference vehicles or defects of referencevehicles.